• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1003-1004
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• 2007

This paper deals with the PM performance evaluations in a variable flux memory motor (VFMM) using a coupled finite element method (FEM) and Preisach modeling, which is presented to analyze the magnetic characteristics of permanent magnets. The focus of this paper is the operation characteristics evaluation relative to magnetizing direction and quantity of permanent magnets on redemagnetization condition in a variable flux memory motor(VFMM).

• 대한기계학회논문집A
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• 제25권6호
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• pp.938-948
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• 2001

In this paper, we present an exoskeletal haptic device named SKK Hand Master. This device is directly driven linkages actuated with small ultrasonic motors. By adopting ultrasonic motors that have advantageous features useful for cybernetic actuators, a compact haptic device containing whole driving packages can be established without additional power transmissions such as tendons. Methods for measuring joint postures and joint torques are developed and a new control strategy called PWM/PS is proposed to overcome intrinsic disadvantages such as hysteresis. Issues regarding design and construction of the device are addressed and several results of experiments for the evaluations of performance are included.

• International Journal of Contents
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• 제12권2호
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• pp.37-41
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• 2016

In this paper, we propose a friend recommendation scheme that takes into consideration the attribute information of a POI and a user's movement patterns. The proposed scheme broadly consists of a part that filters out other users who have different preferences by calculating preferences using the attribute information of users and a part that finds a moving trajectory close to that of a user with a pattern-matching scheme. To verify the superiority of the proposed scheme, we compare it with existing schemes through various performance evaluations.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.584-589
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• 2008

A bi-modal tram has been developing to consist of articulated-two cars propelled by CNG hybrid (series type) in Korea since 2003. All wheels are driven by electrical motors independently, which can eliminate differential gears to reduce turning radius and make low floor to provide the old and the handicapped with easy access. In the bi-modal tram, therefore, reduction gear unit is key technology to make low floor and drive wheels independently. This study was aimed at performance evaluations of the reduction gear unit for the bi-modal tram. Oil leakage, oil temperature, vibration, acoustic noise in idle operations were measured for the reduction gear unit of the bimodal tram.

• Nuclear Engineering and Technology
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• 제35권2호
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• pp.121-132
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• 2003

To reduce the construction cost and enhance the safety of sodium cooled liquid metal reactors, various kinds of new design concepts were evaluated using the KALIMER operation condition. The required equipment sizes were set for plant electricity output to be similar to that of KALIMER. The evaluations were made focusing on the plant performance and implementation practicality. Each design concept was evaluated for the concept itself and design impacts to interfacing systems. Through the evaluation of the concepts, it was found that the most favorable design concept is the integrated steam generator with forced convection using lead bismuth as the intermediate heat transfer fluid between the primary sodium tube and feed water/steam tube in the steam generator.

• International journal of advanced smart convergence
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• 제10권1호
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.317-319
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• 2022

Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.

• ETRI Journal
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• 제46권3호
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• pp.513-525
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• 2024

Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

• 한국컴퓨터정보학회논문지
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• 제25권9호
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• pp.91-100
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• 2020

본 논문은 네트워크 품질에 대한 서비스의 품질과 성능을 평가할 수 있는 분산형/탈중앙 스토리지에 오디오와 비디오를 포함하는 멀티미디어 스트리밍 서비스의 프로토타입을 설계하고 구현한 통합된 평가 프레임워크를 제안한다. 본 논문의 평가 프레임워크는 기존 클라이언트·서버 구조의 확장성과 단일 장애 지점의 문제를 극복할 수 있도록 멀티미디어 스트리밍 서비스에 분산형 스토리지를 적용하였으며, 서비스 품질을 측정하고 향상 시키는 중요한 지표에 초점을 맞추었다. 특히 탈중앙 스토리지 기반의 멀티미디어 콘텐츠 스트리밍 서비스에서 스트리밍의 품질과 성능을 평가하기 위한 성능 지표를 측정할 수 있을 뿐만 아니라 네트워크 가상화 기술을 이용하여 네트워크 품질을 조정할 수 있다. 실험 결과에 따르면 제안된 프레임워크는 단일 호스트 컴퓨터에 탈중앙 스토리지 기반 스트리밍 서비스를 구축하고 운영하는 데 있어 오버헤드가 낮음을 보여주었으며, 평가 가능한 시스템 규모의 확장성을 검증하였다.

• 디지털융복합연구
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• 제13권11호
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• pp.337-348
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• 2015

터치 인터페이스 입력방식에서 메뉴를 마우스를 이용하여 입력하는 것 보다 터치입력 방식이 의도하지 않는 터치와 입력의 어려움이 증가하고 있다. 본 연구에서는 버튼메뉴의 최소 형상버튼을 기준으로 형태와 크기변화에 따라서 사용성 평가를 분석하고자 한다. 적용방법으로는 터치 입력방식의 인터페이스 디자인에서 활용 할 수 있도록 회귀 모형식과 인터페이스 인간 수행 평가방법의 대표적인 모형인 피츠의 법칙(Fitts' Law)의 비교분석을 통해서 더욱 효과적인 정량적 수행예측 평가 모형식 적용을 통해서 가능성을 확인하고자 했다. 따라서 터치 환경에서 적용할 수 있는 버튼의 형상과 크기변화에 따른 사용자의 사용시간을 고려한 수행예측시간을 디자인에 반영할 수 있다.